def rot_lon_lat(self, lon, lat):
""" Rotate the specified lon/lat to the equatorial grid. """
v1 = DoubleVector()
v2 = DoubleVector()
Background.rot_grid(v1, v2, DoubleVector([lon]), DoubleVector([lat]),
self.center)
return v1[0], v2[0]
def setup(self):
SkyIntegrator.set_tolerance(self.tolerance)
exp = self.sa.exposure.exposure
psf = self.sa.psf
if len(self.dmodel) == 1:
self.bgs = [Background(self.dmodel[0], exp[0], exp[1])]
else:
self.bgs = map(Background, self.dmodel, exp)
def set_diffuse(diffusefilename='galdiffuse', exposure=1e10):
if 'GLAST_EXT' in os.environ and diffusefilename == 'galdiffuse':
diffusefilename = os.path.join(os.environ['GLAST_EXT'], 'extFiles',
'v0r7', 'galdiffuse', 'GP_gamma.fits')
diffuse = DiffuseFunction(diffusefilename)
background = Background(diffuse, exposure)
PointSourceLikelihood.set_diffuse(background)
return (diffuse, background) # return to keep references
def reload_data(self,bands):
exp = self.sa.exposure.exposure
ns = self.nsimps
nm = len(self.models)
rd = self.roi_dir
front_bgs = [Background(model.get_dmodel(0),exp[0]) for model in self.bgmodels]
back_bgs = [Background(model.get_dmodel(1),exp[1]) for model in self.bgmodels]
for nband,band in enumerate(bands):
if not band.has_pixels:
band.pi_evals = 0
band.bg_pix_counts = 0
continue
#for bg in bgs: bg.set_event_class(band.ec)
bgs = back_bgs if band.ec else front_bgs
band.pi_evals = N.empty([len(band.wsdl),nm,ns + 1])
for ne,e in enumerate(band.bg_points):
for nbg,bg in enumerate(bgs):
bg.setEnergy(e)
band.pi_evals[:,nbg,ne] = N.asarray(bg.wsdl_vector_value(band.wsdl))
#there really needs to be a reconciliation between generated and updating
band.mo_evals = N.empty([nm,ns + 1])
for n,m in enumerate(self.models):
band.mo_evals[n,:] = m(band.bg_points)
band.bg_counts = (band.ap_evals * band.mo_evals).sum(axis = 1)
band.bg_all_counts = band.bg_counts.sum()
band.pi_evals *= (band.b.pixelArea() * band.bg_vector)
band.bg_pix_counts = (band.pi_evals * band.mo_evals).sum(axis = 2)
band.bg_all_pix_counts = band.bg_pix_counts.sum(axis=1)
def setup(self):
exp = self.sa.exposure.exposure
psf = self.sa.psf
if len(self.dmodel) == 1:
self.bg = [Background(self.dmodel[0], exp[0], exp[1])]
self.bgc = [
BackgroundConvolution(self.roi_dir,
self.bg[0],
psf,
npix=self.npix,
pixelsize=self.pixelsize)
]
else:
self.bg = map(Background, self.dmodel, exp)
self.bgc = [
BackgroundConvolution(self.roi_dir,
bg,
psf,
npix=self.npix,
pixelsize=self.pixelsize)
for bg in self.bg
]